Book Image

Apache Spark 2: Data Processing and Real-Time Analytics

By : Romeo Kienzler, Md. Rezaul Karim, Sridhar Alla, Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen Mei
Book Image

Apache Spark 2: Data Processing and Real-Time Analytics

By: Romeo Kienzler, Md. Rezaul Karim, Sridhar Alla, Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen Mei

Overview of this book

Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: • Mastering Apache Spark 2.x by Romeo Kienzler • Scala and Spark for Big Data Analytics by Md. Rezaul Karim, Sridhar Alla • Apache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbook
Table of Contents (23 chapters)
Title Page
Copyright
About Packt
Contributors
Preface
Index

Appendix 1. Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

Modern Scala Projects

Ilango Gurusamy

ISBN: 9781788624114

  • Create pipelines to extract data or analytics and visualizations
  • Automate your process pipeline with jobs that are reproducible 
  • Extract intelligent data efficiently from large, disparate datasets 
  • Automate the extraction, transformation, and loading of data
  • Develop tools that collate, model, and analyze data
  • Maintain the integrity of data as data flows become more complex
  • Develop tools that predict outcomes based on “pattern discovery”
  • Build really fast and accurate machine-learning models in Scala

Apache Spark Deep Learning CookbookAhmed Sherif and Amrith Ravindra

ISBN: 9781788474221

  • Set up a fully functional Spark environment
  • Understand practical machine learning and deep learning concepts
  • Apply built-in machine learning libraries within Spark
  • Explore libraries that are compatible with TensorFlow and Keras
  • Explore NLP models such as Word2vec and TF-IDF on Spark
  • Organize dataframes for deep learning evaluation
  • Apply testing and training modeling to ensure accuracy
  • Access readily available code that may be reusable